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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A red algal polysaccharide influences the multicellular development of the choanoflagellate Salpingoeca rosetta

The choanoflagellate Salpingoeca rosetta exemplifies the capacity of marine microeukaryotes to integrate environmental cues into their life histories. Some of the cues that S. rosetta detects are lipids from their bacterial prey that induce the development of multicellular colonies called rosettes. In the aquatic environments where S. rosetta would encounter bacterial cues, microbial communities gain refuge and food from algae. For example, microbes in coastal environments benefit from macroalgae that annually release ∼10 14 g of carbon, primarily in the form of polysaccharides that comprise ∼80% of dissolved organic carbon in surface waters. Despite the ecological impact of algae and historical descriptions of choanoflagellates attached to algae, the influence of algae on choanoflagellate life history transitions has remained unexplored. Here, we report that porphyran, a polysaccharide produced by the red macroalga Porphyra umbilicalis, induces multicellular development in S. rosetta. We first noticed this response when S. rosetta formed multicellular rosette colonies while growing in media prepared from P. umbilicalis, even though rosette-inducing bacteria were absent. By biochemically purifying extracts of P. umbilicalis, we identified porphyran as the rosette-inducing factor. This response provides a biochemical insight that indicates algal polysaccharides may serve as cues to mediate associations between choanoflagellates and algae. Moreover, this observation complements evidence from environmental and geochemical studies that show the impact that algae have exerted on the ecology and evolution of eukaryotes, including a rise in algal productivity during the origin of animals, the closest living relatives of choanoflagellates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The TW Hya Rosetta Stone Project. I. Radial and Vertical Distributions of DCN and DCO{sup +}

Molecular D/H ratios are frequently used to probe the chemical past of solar system volatiles. Yet it is unclear which parts of the solar nebula hosted an active deuterium fractionation chemistry. To address this question, we present 0."2–0."4 Atacama Large Millimeter/submillimeter Array (ALMA) observations of DCO{sup +} and DCN 2–1, 3–2, and 4–3 toward the nearby protoplanetary disk around TW Hya, taken as part of the TW Hya Rosetta Stone project, augmented with archival data. DCO{sup +} is characterized by an excitation temperature of ~40 K across the 70 au radius pebble disk, indicative of emission from a warm, elevated molecular layer. Tentatively, DCN is present at even higher temperatures. Both DCO{sup +} and DCN present substantial emission cavities in the inner disk, while in the outer disk the DCO{sup +} and DCN morphologies diverge: most DCN emission originates from a narrow ring peaking around 30 au, with some additional diffuse DCN emission present at larger radii, while DCO{sup +} is present in a broad structured ring that extends past the pebble disk. Based on a set of simple parametric disk abundance models, these emission patterns can be explained by a near-constant DCN abundance exterior to the cavity, and an increasing DCO{sup +} abundance with radius. In conclusion, the ALMA observations reveal an active deuterium fractionation chemistry in multiple disk regions around TW Hya, but not in the cold planetesimal-forming midplane and in the inner disk. More observations are needed to explore whether deuterium fractionation is actually absent in these latter regions, and if its absence is a common feature or something peculiar to the old TW Hya disk.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid Phase Transitions of Thermotropic Glycolipid Quasicrystal and Frank‐Kasper Mesophases: A Mechanistic Rosetta Stone

Abstract Experimental results are presented that serve to lower the barrier for developing the science and technology of non‐classical thermotropic glycolipid mesophases, which now include dodecagonal quasicrystal (DDQC) and Frank–Kasper (FK) A15 and σ mesophases that can be produced under mild conditions from a versatile class of sugar‐polyolefin conjugates. By employing “alloys” comprised of mono‐ and disaccharide‐polyolefin conjugates, and optionally with vitamin E as a small molecule phase modulator, we report the spontaneous formation of stable A15 mesophases at ambient temperature. We further document a rich thermotropic phase map that includes DDQC, A15, and σ mesophases of tunable periodicity that are connected through rapid thermotropic phase transitions as a function of increasing temperature in the order: liquid‐like packing (LLP)→DDQC → A15→σ→ disorder. This first direct observation of a rapid thermotropic A15→σ phase transition provides support for a diffusionless martensitic process proceeding through strain‐induced introduction of planar defects into the A15 lattice.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Rapid Phase Transitions of Thermotropic Glycolipid Quasicrystal and Frank‐Kasper Mesophases: A Mechanistic Rosetta Stone

Abstract Experimental results are presented that serve to lower the barrier for developing the science and technology of non‐classical thermotropic glycolipid mesophases, which now include dodecagonal quasicrystal (DDQC) and Frank–Kasper (FK) A15 and σ mesophases that can be produced under mild conditions from a versatile class of sugar‐polyolefin conjugates. By employing “alloys” comprised of mono‐ and disaccharide‐polyolefin conjugates, and optionally with vitamin E as a small molecule phase modulator, we report the spontaneous formation of stable A15 mesophases at ambient temperature. We further document a rich thermotropic phase map that includes DDQC, A15, and σ mesophases of tunable periodicity that are connected through rapid thermotropic phase transitions as a function of increasing temperature in the order: liquid‐like packing (LLP)→DDQC → A15→σ→ disorder. This first direct observation of a rapid thermotropic A15→σ phase transition provides support for a diffusionless martensitic process proceeding through strain‐induced introduction of planar defects into the A15 lattice.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

La$_{2-x}$Ba$_x$CuO$_4$ as a superconducting Rosetta Stone

The high-temperature superconductivity in layered cuprates discovered by Bednorz and Müller arrived as a shock. Gradually, the presence of competing orders, such as antiferromagnetism and charge order, were discovered; however, the relationship to the superconductivity has been confusing. Importantly, it so happens that the original cuprate superconductor family La$_{2-x}$Ba$_x$CuO$_4$ contains all of the relevant phases, with extreme competition among them, and analysis of these phases provides strong clues to the nature of the superconductivity in cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of protein–protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein–protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning–based methods to unlock the widespread application of designed protein–protein interfaces and self-assembling protein nanomaterials in biotechnology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

De novo design of small beta barrel proteins

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy–based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Robust deep learning–based protein sequence design using ProteinMPNN

Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning–based protein sequence design method, ProteinMPNN, that has outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4% compared with 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using x-ray crystallography, cryo–electron microscopy, and functional studies by rescuing previously failed designs, which were made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target-binding proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Better together: Elements of successful scientific software development in a distributed collaborative community

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

K in an Urban World: New Contexts for Hydraulic Conductivity

Abstract Hydraulic conductivity ( K ) is a key hydrologic parameter widely recognized to be difficult to estimate and constrain, with little consistent assessment in disturbed, urbanized soils. To estimate K , it is either measured, or simulated by pedotransfer functions, which relate K to easily measured soil properties. We measured K in urbanized soils by double‐ring infiltrometer ( K dring ), near‐saturated tension infiltrometry ( K minidisk ), and constant head borehole permeametry ( K borehole ), along with other soil properties across the major soil orders in 12 United States cities. We compared measured K with that predicted from the pedotransfer function, ROSETTA. We found that regardless of soil texture, K dring was consistently larger than K minidisk ; with the latter having slightly less sample variance. K borehole was dependent upon specific subsurface conditions, and contrary to common expectations, did not always decrease with depth. Based on either soil textural class, or percent textural separates (sand, silt clay), ROSETTA did not accurately predict measured K for surface nor subsurface soils. We go on to discuss how K varies in urban landscapes, the role of measurement methods and artifacts in the perception of this metric, and implications for hydrologic modeling. Overall, we aim to inspire consistency and coherence when addressing K ‐related challenges in sustainable urban water management.

Shuster, W. D.↗
DOE OSTI2025

Thermophilic Chassis-Enabled High-Throughput Selection of a Thermostable Fluorogenic Reporter

Thermostable proteins show increased shelf life and performance at elevated temperatures and under harsh conditions, resulting in lower costs for various industrial and biotechnological applications. However, due to a limited understanding of the relationship between stability and function, protein stabilization remains primarily a trial-and-error approach. Therefore, building a combinatorial library of mutations predicted to improve stability, followed by experimental testing, represents a markedly improved methodology. However, the lack of high-throughput approaches to screen even a moderately sized library presents a major bottleneck in the field. Here, in this study, we use a thermophile, Parageobacillus thermoglucosidasius (Ptherm) to rapidly screen combinatorial libraries consisting of rationally designed thermostabilizing mutations (∼10 3 –10 4 ) of a mesophilic fluorescent reporter, Y-FAST. On a Petri dish, microbial growth at an elevated temperature and exposure to fluorogen yielded several colonies of Ptherm that showed distinct fluorescence at 55 and 68 °C in our two sequentially generated libraries using Rosetta and ProteinMPNN, respectively. The Y-FAST variants isolated from fluorescent colonies were brighter than Y-FAST and showed higher resistance to thermal and chemical denaturation. AlphaFold-predicted structures and MD simulations revealed stability-enhancing salt bridges and hydrogen bond networks in the isolated FAST variants. The moderately thermostable FAST (tsFAST) and hyperstable FAST (hsFAST) were then demonstrated as translation reporters for protein expression and folding at elevated temperatures, such as 55 and 68 °C. Our approach of combinatorial library generation and high-throughput screening in a thermophilic chassis could, in principle, be extended to other proteins fused to these translation reporters. Furthermore, the hsFAST protein is small─half the size of the green fluorescent protein─and does not require oxygen for maturation, making it ideal for engineering extremophilic anaerobes for biosensing and bioconversion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structural characterization and computational analysis of PDZ domains in Monosiga brevicollis

Abstract Identification of the molecular networks that facilitated the evolution of multicellular animals from their unicellular ancestors is a fundamental problem in evolutionary cellular biology. Choanoflagellates are recognized as the closest extant nonmetazoan ancestors to animals. These unicellular eukaryotes can adopt a multicellular‐like “rosette” state. Therefore, they are compelling models for the study of early multicellularity. Comparative studies revealed that a number of putative human orthologs are present in choanoflagellate genomes, suggesting that a subset of these genes were necessary for the emergence of multicellularity. However, previous work is largely based on sequence alignments alone, which does not confirm structural nor functional similarity. Here, we focus on the PDZ domain, a peptide‐binding domain which plays critical roles in myriad cellular signaling networks and which underwent a gene family expansion in metazoan lineages. Using a customized sequence similarity search algorithm, we identified 178 PDZ domains in the Monosiga brevicollis proteome. This includes 11 previously unidentified sequences, which we analyzed using Rosetta and homology modeling. To assess conservation of protein structure, we solved high‐resolution crystal structures of representative M. brevicollis PDZ domains that are homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains. To assess functional conservation, we calculated binding affinities for mbGIPC, mbSHANK1, mbSNX27, and mbDLG‐3 PDZ domains from M. brevicollis . Overall, we find that peptide selectivity is generally conserved between these two disparate organisms, with one possible exception, mbDLG‐3. Overall, our results provide novel insight into signaling pathways in a choanoflagellate model of primitive multicellularity.

Gao, Melody↗